最新刊期
卷 ， 期 5 ， 2007
- 摘要：<正>This special issue brings together papers that were presented in the 9th International Symposium on Physical Measurements and Signatures in Remote Sensing（ISPMSRS05）, Beijing,2005.
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发布时间：2021-06-10 - 摘要：Leaves are a basic component of plant canopy and their optical properties have great influence on canopy reflectance spectra that can be obtained by remote sensors.In principle,the reflectance spectra are determined by the biochemical constituents and biophysical structure of the leaves.The accurate estimation of leaf structure may help to separate its contribution to leaf spectra and improve the inversion of leaf biochemical information that is widely used in many fields.In this paper,leaf biophysical structure is described as an assumed dimensionless variable-leaf mesophyll structure parameter noted as N.It is one of four input variables of the PROSPECT model,a well-known within-leaf radiative tranfer model.Model simulated spectra show that it has great effect on leaf reflectance and transmittance spectra ranging from visible to shortwave infrared radiation.Three methods,including two empirical methods and one model inversion method,are examined and compared.Results show that the calculated N by model inversion method can provide least RMSE between measured spectra and model simulated spectra if leaf biochemical variables are given.Its value is generally less than Ns calculated by empirical methods based on its relation with specific leaf area（SLA）.Furthermore,four bands,550nm,816nm,1210nm and 1722nm,are selected to be sensitive for N estimation using stepwise multiple linear regression（SMLR）.关键词：mesophyll structure;rice;PROSPECT model;Spectra
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发布时间：2021-06-10 - 摘要：Polarized and bi-directional reflectance of corn leaves from northeast China were collected with multi-angle reflectance detection instrument in the laboratory.This instrument has the ability to measure polarized reflectance and bi-directional reflectance of targets at various viewing zenith angles,light incidence zenith angles and azimuth angles.We analyzed the relationship between polarized and bi-directional reflectance according to the geometric characters listed above,and found that bi-directional reflectance is approximate half the sum of maximum and minimum polarized reflectance.The relationship between bi-directional and polarized reflectance has a direct relation to the sensor’s viewing geometry.This study describes a new method for vegetation remote sensing detection and monitoring,and also provides a theoretical basis for further research on the relationship between polarized reflectance and bi-directional reflectance for remote sensing technology.关键词：polarized light;polarized reflectance;bi-directional reflectance;corn leaf
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发布时间：2021-06-10 - 摘要：The application of spectral properties as a diagnostic tool in nutrient deficiency diagnosis requires further understanding of the relationship between spectral properties and nutrient concentration in plant tissue.Therefore,to examine the effect of variable potassium fertilization on corn（Zea mays L.） leaves and the response on leaf spectral reflectance.We designed an experiment to examine the effect variable amounts of potassium fertilization during four stages of corn growth.Our results showed that the difference in potassium leaf content is significant at the 0.05 probability level with increasing potassium fertilization.We then examined the correlation between corn leaves spectra reflectance and nutrient content as a function of variable levels of potassium fertilization over the entire corn growing season by potted plant experiment.Digital models were constructed to assess potassium content in leaves by utilizing leaves spectral reflectance in the booting stage Our results showed that there was a correlation between the spectral reflectance of corn leaves and corresponding leaf inner moisture,chlorophyll and other nutrient content including nitrogen,phosphorous,potassium,calcium,magnesium,copper,iron,manganese,and zinc.These differences in the spectral reflectance held for the entire growing season.730—930 nm and 960—1100 nm were defined as sensitive wave bands to assess potassium nutrition condition in booting stage,and spectral variables including R767+R1057,（R767+R1057）/（logR767+logR1057） and（R767-R1057）/（logR767-logR1057） could predict accurately corn leaf potassium-content in the booting stage.Our analysis indicated a correlation between various components in the inner leaves and spectral reflectance at this stage.Inflection points occurred at 410nm,550nm,710nm,950nm in every curve.When correlations between the various components were high,their spectra correlation curves were coincident or symmetrical.关键词：Spring corn;potassium fertilization;nutrients;spectral reflectance;correlation
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发布时间：2021-06-10 - 摘要：The potential of EO-1 Hyperion data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of forest structural variables in the Longmenhe broadleaved forest natural reserve,located in the Three Gorges region（China）,is studied in this paper.Based on the principle of Li-Strahler geometric-optical model,we derive the per-pixel reflectance as being a linear combination of four scene components（sunlit canopy/sunlit background and shaded canopy/shaded background）.The fraction of each component is subsequently related to several forest structural attributes.With the advantage of having hyperspectral data,we use linear spectral unmixing to separate the above classes present in an atmospherically corrected Hyperion image with support of extensive in situ measurements.In addition,we include DEM derived parameters（slope and aspect） and measured canopy structural parameters for different forest communities to invert the geometric-optical model and retrieve the pixel-based variables forest crown closure（CC） and crown diameter（CD）.In total 37 sample plots collected in the Longmenhe study region are used for validation,and the results of the above parameters show a good agreement（e.g.,R2CC=0.61/RMSE=0.046;R2CD=0.39/RMSE=0.984）.关键词：EO-1 hyperion;forest structural variable;crown closure;crown diameter;geometric-optical model;linear spectral unmixing;Three Gorges region
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发布时间：2021-06-10 - 摘要：Getting reliable and up-to-date land cover information is essential to model the Earth system.In this respect,the observation capabilities of medium spatial resolution sensors like MODIS or MERIS are offering new land cover mapping possibilities because of the unprecedented resolutions of these sensors.This paper illustrates how the combination of the spatial（300m pixel size）,spectral（15 narrow bands in the visible and NIR）,and temporal（revisit time 2-3 days） dimensions of MERIS can be used to retrieve sub-pixel fractional land cover composition over heterogeneous areas.Three MERIS FR Level 1b scenes acquired over The Netherlands in April,July and August 2003 were used to derive fractional composition of the main land cover types present in The Netherlands.A linear spectral unmixing with an optimized number of endmembers per pixel was applied both in a mono-and in a multi-temporal way.A morphological eccentricity index（MEI） was used to explore the MERIS spatial dimension and,subsequently,to support the selection of the endmembers.The Dutch land use database（LGN5）,which has a grid structure with a pixel size of 25m,was used as a reference in this study.Classification accuracy was assessed both at per-pixel and at sub-pixel level because of the availability of this high resolution reference data.The best classification results were obtained for the combined image of April and July with a classification accuracy of about 58%.In general,sub-pixel and per-pixel classification accuracies were found to be similar.Spectral confusion was detected for several classes and dates indicating that the phenological status plays an important role in choosing the optimal combination of acquisition dates and the land cover classes that can be properly identified.关键词：MERIS;linear spectral unmixing;endmembers;morphology;sub-pixel
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发布时间：2021-06-10 - 摘要：LAI（leaf area index） and LAD（leaf angle distribution） are two important parameters determining vegetation canopy structure.In computer simulations of vegetation canopies,these two parameters are the controlling parameters that render the 3D vegetation scene.In this paper,a computer graphics method,Modified Extended L-system（MELS）,is used to render an architecturally realistic leaf canopy（grass） and tree canopy（aspen）,that are based on measured structure data of typical grass and aspen trees.A radiosity-graphics combined model（RGM） is then used to calculate the radiation regime of the simulated 3D realistic structure scene,including canopy directional reflectance and spectrum in visible and NIR regions.Two aspen tree scenes are simulated:one where the underlying surface is soil and another where the underlying surface is grass and soil.Then,distributed characteristics of canopies BRF（bi-directional reflectance factor） for the two kinds of scenes are analyzed.However,for realistically structured trees,the radiosity method cannot simulate a large-scale scene because there are too many variables to be processed,so one solution is to simplify the tree crown,making it possible to simulate the canopy BRF at a larger scale.So,we conclude that computer simulations can obtain the radiation regime of forest canopies with some kinds of underlying surfaces,making computer simulation a good way of providing directional reflectance.关键词：bidirectional reflectance factor（BRF）;radiosity;computer simulation;GOMS
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发布时间：2021-06-10 - 摘要：In this paper,we evaluate the capability of a multi-scattering microwave emission model that includes the Dense Media Radiative Transfer Model（DMRT） and Advanced Integral Equation Model（AIEM） to simulate dry snow emission with the Matrix Doubling approach.We compared the predictions of this model with ground experimental measurements.The comparison showed that our snow microwave emission model agreed well with the experimental measurements.In order to develop retrieval snow properties:snow depth or snow water equivalence（SWE） retrieval algorithm,we carried out the sensitivity test between the emission models with the different scattering-order:the zeroth-order,the first-order and the multi-scattering models.The results indicated that the multi-scattering effects have to be taken into account in the snow emission model,especially for large grain size.Due to the complexity of the multi-scattering model,we developed a parameterized inversion model using our multi-scattering emission model with a wide range of snow and under-ground properties for algorithm development purpose.关键词：snow;passive microwave remote sensing;parameterization
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发布时间：2021-06-10 - 摘要：The availability of full polarimetric SAR data made it become possible to use three complex elements（HH,HV,VV） of the polarimetric scattering matrix to reduce speckle in multilook full polarimetric SAR images.As a typical example,the multilook polarimetric whitening filter（MPWF） is regarded as optimal.However,to enhance the precision of parameter estimation and meanwhile detect the structural feature adaptively,windowing algorithm must be needed when filtering.In this paper,two new windowing approaches are introduced and NASA SIR-C/X-SAR,L band,four-look processed polarimetric SAR data of the Tian-Mountain Forest is used for simulation.Experimental results demonstrate the effectiveness of these methods both on speckle reduction and preservation of texture information.关键词：MPWF;Structure detection;speckle;Multilook polarimetric SAR
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发布时间：2021-06-10 - 摘要：The ability of remote sensing data to acquire measurements of land surfaces at different spatial,spectral and temporal scales renders it a major source of land cover information.The process of relating pixels in a satellite image to known land cover is referred to as image classification.Support Vector Machines（SVMs） represent one of the new generation land cover classification techniques.There are three commonly used SVMs namely:linear,polynomial and radial basis function（Gaussian） SVM classifiers,whose successful deployment is dependant on the selection of respective optimum parameters.The voluminous nature of remote sensing data renders the identification of these parameters slow and tedious.In this paper,a new data reduction technique that optimizes remote sensing data for SVM classification is proposed.This research shows that the quantity of data needed to derive the SVM parameters can be reduced without adversely affecting the land cover classification accuracy.Data reduction was successfully applied to polynomial and radial basis function（RBF） SVM classification.Linear SVM classification results however,resulted in significantly poorer classification accuracies.关键词：Support Vector Machines;data reduction;land cover mapping
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发布时间：2021-06-10 - 摘要：This paper conveys the application of genetic algorithms（GA） which are used to improve unsupervised training and thereby increase the classification accuracy of remotely sensed data. The genetic competitive learning algorithm（GA-CL）, an integrated approach of the GA and simple competitive learning（CL） algorithm, was developed for unsupervised training. Genetic algorithms are used to improve the training results for the algorithm. GA is used to prevent falling in the local minima during the process of cluster prototypes learning. The evaluation of the algorithm uses the Jeffries-Matusita（J-M） distance, a measure of statistical separability of pairs of trained clusters. Experiments on Landsat Thema-tic Mapper（TM） data show that the GA improves the simple competitive learning algorithm. Comparisons with other unsupervised training algorithms, the K-means, GA-K-means, and the simple competitive learning algorithm are provided.关键词：unsupervised training;clustering algorithms;artificial neural networks;competitive learning algorithms;genetic algorithms
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发布时间：2021-06-10 - 摘要：In this paper,we present the results of our research to evaluate the accuracy of the back propagation neural network method to classify forest vegetation using a 27 July 2001 Landsat 7 ETM+ image of the Manhanshan Forestry Center.The type and quantitative accuracy of the back propagation neural network are compared with the maximum likelihood,the simple and the complex unsupervised classification methods.The total cover type accuracy of back propagation neural network classification is 70.5%,the total quantity accuracy is 84.65%,and the KAPPA coefficient is 0.6455.Our results indicate that the total type accuracy increases 10.5%、32% and 33% respectively compared to the other three classification methods.Total quantitative accuracy increases 5.3%.It is evident that the classification quality of the back propagation neural network is better than the other methods.Therefore,the back propagation neural network is an effective and accurate method of classifying forest vegetation.关键词：remote sensing;classification;forest vegetation;back propagation artificial neural network
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发布时间：2021-06-10 - 摘要：This paper presents a software system,MODISoft,which can process MODIS 1B data automatically to generate various products covering the whole China.Some new algorithms were proposed to overcome the shortcomings of NASA MODIS standard products.The strength of the LAI retrieval method is that it avoids using two incompatible methods in NASA LAI product.The algorithm for estimating both land surface reflectance and aerosol optical depth is based on mutli-temporal observations and produces more accurate products.The cloud mask algorithm detects low clouds better.Some of key inputs for these algorithms are localized over China.This system also produces some new products that are not available in the standard NASA product suite,including the forest burned scar and PAR.The data processing system is operationally run in the National Scientific Data Center for Resources and Environment,Chinese Academy of Sciences.关键词：MODIS;data processing system;remote sensing
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发布时间：2021-06-10 - 摘要：The laval stage of the fox tapeworm Echinococcus multilocularis causes the rare but fatal liver disease Human Aleveolar Echinococcosis（AE）.The tapeworm is transmitted in a predator-prey cycle between foxes（or dogs） and a range of small mammal species and is restricted to specific landscape conditions.HAE is endemic in parts of central China with prevalence rates of up to 15% in some villages.This paper describes how remotely sensed data have been used to develop spatially explicit risk maps for the disease based on landscape characterization.The results show that the proximity of grassland or shrubland areas to human settlements,derived from the remotely sensed data,was a major risk factor for HAE related to the spatial distribution of suitable habitat for the small mammal intermediate hosts.关键词：tapeworm;remote sensing;Parasitic Disease;China
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发布时间：2021-06-10 - 摘要：This paper is concerned with a new method for mapping taiga forests using high-resolution remotely sensed data and mathematical models.New technologies are suggested for processing space-acquired images.Mapping results for the northern Irkutsk region（Ust-Ilimsk district） are presented.关键词：remote sensing;forest mapping;mathematical models
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发布时间：2021-06-10 - 摘要：Normalized Difference Vegetation Index（NDVI） from satellite data and ground mesh（cell） data（10km×10km） for temperature and precipitation over 20 years（1981—2000） were used to investigate the relationships among NDVI,temperature,and precipitation.In addition,the study area was divided into eight climate zones based on the ground mesh data for temperature and precipitation.The zones with little precipitation-Zone 1,2,and 3-were categorized into 10 classes using NDVI data.Moreover,NDVI change for each class of Zone 1,2,and 3 during 15 years（1983—1998） was analyzed.The results indicate the aggravation of desertification.关键词：aggravation;NDVI;precipitation;temperature
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发布时间：2021-06-10 - 摘要：In this paper,a new approach for classification of multitemporal satellite data sets,combining multispectral and change detection techniques is proposed.The algorithm is based on the nearest neighbor method and derived in order to optimize the average probability for correct classification,i.e.each class is equally important.The new algorithm was applied to a study area where satellite images（SPOT and Landsat TM） from different seasons were used.It showed that using five seasonal images can substantially improve the classification accuracy compared to using a single image.As a large scale application,the approach was applied to the Dal River drainage basin.As the distributions for different classes are highly overlapping it is not possible to get satisfactory accuracy at pixel level.Instead it is necessary to introduce a new concept,pixel-wise probabilistic classifiers.The pixel-wise vectors of probabilities can be used to judge how reliable a traditional classification is and to derive measures of the uncertainty（entropy） for the individual pixels.The probabilistic classifier gives also unbiased area estimates over arbitrary areas.It has been tested on two test sites of arable land with different characteristics.关键词：nonparametric classification;nearest neighbor method;probabilistic classifier;agricultural crops;quality assessment;multitemporal images;remote sensing;drainage basin
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发布时间：2021-06-10 - 摘要：In this paper,a new hyperspectral data model that estimates chlorophyll-a concentration（Chla） in Taihu Lake of summer is proposed.The model was developed based on measurement in situ in July 2004,and was validated by hyperspectral data in August 2004.Water samples were collected by Wuxi Taihu Lake Environment Monitoring Station and covered the typical water areas.At each site,hyperspectral data were measured ten times by field spectroradiometer ASD FieldSpec,and were converted into remote sensing reflectance.Different band combinations were calculated and compared,and the normalized band index was selected because it is more explicable.The model built by data in July 2004 is Chla（μg/L）=EXP（2.478+16.378N66）,where N66 is（R696-R661）/（R696+R661）.Goodness-of-fit statistics of the model R2 is 0.9051,and p<0.0001.Compared with other models,this one is more stable,and is of less absolute error when used to estimate Chla in August 2004.The works in the paper also showed that hyperspectral data model can be used to estimate Chla by month in the summer of Taihu Lake.关键词：chlorophyll-a;hyperspectral data;taihu lake;water environment
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发布时间：2021-06-10
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